Automation of Data Collection for Measuring The Quality of E-Commerce

The research aims to help managers in information gathering web log visitors based on traffic data, building automation data for determining the needs of e-Commerce extensibility, and design of information systems in the process of database interaction diagrams to show the control chart. Web monitoring is not so complex that requires a variety of tools (tools / applications / programs). Data collection in the form of traffic data and transaction data obtained automation. Data collected by the web application traffic and data traffic of e-Commerce transactions themselves. For a company whose goal is not just appear and serve customers, but is able to know the customer desires and business growth observed, this method is very suitable for monitoring quality control chart diagram shown in the form on page E-Commece it. Automation of data collection occurred in real time on information systems, so that the extensibility of e-Commerce report can be continuously monitored. The results demonstrate the extensibility of information systems such as e-Commerce can be applied to other e-Commerce

RANCANG BANGUN SISTEM KUIS ONLINE ADAPTIF SEBAGAI EKSTENSI CONTENT MANAGEMENT SYSTEM

This research describes an adaptive online quiz system that can be utilized as an extension of content management system. With ‘adaptive’ capability, quizzes become more personalized as the question presented are specifically model or designed for students according to their level of proficiency. With this, student will get to know their strength and weaknesses in their study as they will not move to a higher level of difficulty if they fail to score a certain rate. A comparative study among the current adaptive systems is done to identify the adaptive components that they applied, the techniques to implement the adaptive components and also the available features. This Web-based quiz system is an adaptive quiz system for student self-assessment with three main components: Student Model, Domain Model and Adaptation Model. Student model describes the student’s knowledge, domain model represents the teaching domain or the representation of the student model, while adaptation model consists of a set of rules that defines the user’s action. The Stereotypes and Overlay Model techniques are applied to model the student’s knowledge, the Semantic Network is applied to model the Domain Knowledge and the ‘IF-THEN’ rules is applied to model the Adaptation Model. Development of the system using the method of system development life cycle with object-oriented approach. The results of this research is an extension for content management system that can be used as a system of student assessment based on skills, knowledge and preferences of each student Keywords : online quiz, adaptive, student model, domain model, adaptation model, extension, content management syste

Adaptive Model of Personalized Searches using Query Expansion and Ant Colony Optimization in the Digital Library

A system that can provide useful information for users will be able to increase user loyalty. Presentation of useful information can be done by providing the information needed by each user or personalization. Personalization is a form required when the system wants to interact with its users. A personalized system is built based on the needs of each user. In this research, a new personalization model was built for the interaction between digital library systems with users. The proposed model uses adaptive query expansion algorithm and ant colony optimization for searching documents in digital libraries.The model uses metadata to the search process. The metadata consists of titles, abstracts and keywords of the document. The User model is built to monitor user activities when selecting a document link (click) and visit page document (visit). Data of research uses 50 journal documents. The research results that the proposed model improves search scores by 60% and the order of the search documents up to 56%

SISTEM DETEKSI RETINOPATI DIABETIK MENGGUNAKAN SUPPORT VECTOR MACHINE

Diabetic Retinopathy is a complication of Diabetes Melitus. It can be a blindness if untreated settled as early as possible. System created in this thesis is the detection of diabetic retinopathy level of the image obtained from fundus photographs. There are three main steps to resolve the problems, preprocessing, feature extraction and classification. Preprocessing methods that used in this system are Grayscale Green Channel, Gaussian Filter, Contrast Limited Adaptive Histogram Equalization and Masking. Two Dimensional Linear Discriminant Analysis (2DLDA) is used for feature extraction. Support Vector Machine (SVM) and k-Nearest Neighbour (kNN) are used for classification. The test result performed by taking a dataset of MESSIDOR with number of images that vary for the training phase, otherwise is used for the testing phase. Test result show the optimal accuracy are 84% for 2DLDA-SVM and 80% for 2DLDA-kNN. Keywords : Diabetic Retinopathy, Support Vector Machine, Two Dimensional Linear Discriminant Analysis, k-Nearest Neighbour, MESSIDO

SISTEM PENILAIAN RISIKO APLIKASI WEB MENGGUNAKAN MODEL DREAD

Application that is developed by web based, beside has surplus in WWW technology, it has susceptibility side that can be threat too. Susceptibility generate risk and can bring out big trouble even effect big disadvantage The goal of this research is design and build document risk assessment system of threat level and prevention advice. It use DREAD model as method to solve trouble by giving qualified information. This information are used to produce risk level in web application. The result of this research is web application risk assessment system by using DREAD model to know risk threat level and equate perception of web threat risk to application developer, minimize of threat risk and maximize performance of web application. Keywords : DREAD model, web threat risk, web risk assessment syste